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Object Tracking Algorithm Based On The Color Histogram Probability Distribution

机译：基于颜色直方图概率分布的目标跟踪算法

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In order to resolve tracking failure resulted from target's being occlusion and follower jamming caused by objects similar to target in the background, reduce the influence of light intensity. This paper change HSV and YCbCr color channel correction the update center of the target, continuously updated image threshold self-adaptive target detection effect, Clustering the initial obstacles is roughly range, shorten the threshold range, maximum to detect the target. In order to improve the accuracy of detector, this paper increased the Kalman filter to estimate the target state area. The direction predictor based on the Markov model is added to realize the target state estimation under the condition of background color interference and enhance the ability of the detector to identify similar objects. The experimental results show that the improved algorithm more accurate and faster speed of processing.
机译：为了解决背景中与目标相似的物体引起的目标被遮挡和追随者卡塞而导致的跟踪失败，请减小光强度的影响。本文通过改变HSV和YCbCr色彩通道校正目标的更新中心，不断更新图像阈值自适应目标的检测效果，聚类初始障碍物的范围大致，缩短阈值范围，最大程度地检测目标。为了提高检测器的精度，本文增加了卡尔曼滤波器来估计目标状态区域。添加了基于马尔可夫模型的方向预测器，在背景色干扰的条件下实现了目标状态的估计，增强了检测器识别相似物体的能力。实验结果表明，改进算法更准确，处理速度更快。

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